Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable

Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non-intuitive consequences of ion channel-level changes on higher levels of integration

Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable

Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non-intuitive consequences of ion channel-level changes on higher levels of integration

"EDML1": a chronology for the EPICA deep ice core from Dronning Maud Land, Antarctica, over the last 150 000 years.

A chronology called EDML1 has been developed for the EPICA ice core from Dronning Maud Land (EDML). EDML1 is closely interlinked with EDC3, the new chronology for the EPICA ice core from Dome-C (EDC) through a stratigraphic match between EDML and EDC that consists of 322 volcanic match points over the last 128 ka. The EDC3 chronology comprises a glaciological model at EDC, which is constrained and later selectively tuned using primary dating information from EDC as well as from EDML, the latter being transferred using the tight stratigraphic link between the two cores. Finally, EDML1 was built by exporting EDC3 to EDML. For ages younger than 41 ka BP the new synchronized time scale EDML1/EDC3 is based on dated volcanic events and on a match to the Greenlandic ice core chronology GICC05 via <sup>10</sup>Be and methane. The internal consistency between EDML1 and EDC3 is estimated to be typically ~6 years and always less than 450 years over the last 128 ka (always less than 130 years over the last 60 ka), which reflects an unprecedented synchrony of time scales. EDML1 ends at 150 ka BP (2417 m depth) because the match between EDML and EDC becomes ambiguous further down. This hints at a complex ice flow history for the deepest 350 m of the EDML ice core

The moon as a recorder of organic evolution in the early solar system: a lunar regolith analog study

The organic record of Earth older than ∼3.8 Ga has been effectively erased. Some insight is provided to us by meteorites as well as remote and direct observations of asteroids and comets left over from the formation of the Solar System. These primitive objects provide a record of early chemical evolution and a sample of material that has been delivered to Earth's surface throughout the past 4.5 billion years. Yet an effective chronicle of organic evolution on all Solar System objects, including that on planetary surfaces, is more difficult to find. Fortunately, early Earth would not have been the only recipient of organic matter–containing objects in the early Solar System. For example, a recently proposed model suggests the possibility that volatiles, including organic material, remain archived in buried paleoregolith deposits intercalated with lava flows on the Moon. Where asteroids and comets allow the study of processes before planet formation, the lunar record could extend that chronicle to early biological evolution on the planets. In this study, we use selected free and polymeric organic materials to assess the hypothesis that organic matter can survive the effects of heating in the lunar regolith by overlying lava flows. Results indicate that the presence of lunar regolith simulant appears to promote polymerization and, therefore, preservation of organic matter. Once polymerized, the mineral-hosted newly formed organic network is relatively protected from further thermal degradation. Our findings reveal the thermal conditions under which preservation of organic matter on the Moon is viable

Volcanism and the Greenland ice cores: A new tephrochronological framework for the last glacial-interglacial transition (LGIT) based on cryptotephra deposits in three ice cores

Chemical profiles from Greenland ice cores show that the frequency of volcanism was higher during the last glacial-interglacial transition (LGIT) and early Holocene, (17–9 ka b2k) than in any other period during the last 110 kyr. This increased frequency has partly been linked to climate-driven melting of the Icelandic ice sheet during the last deglaciation, with regional isostatic changes thought to alter mantle viscosity and lead to more eruptions. Our study is the first to construct a comprehensive tephrochronological framework from Greenland ice cores over the LGIT to aid in the reconstruction of volcanic activity over this period. The framework is based on extensive high-resolution sampling of three Greenland ice cores between 17.4 and 11.6 ka b2k and comprises a total of 64 cryptotephra deposits from the NGRIP, GRIP and NEEM ice cores. We show that many of these tephras are preserved within the core without an associated chemical signature in the ice, which implies that reconstructions of volcanism based solely on glacio-chemical indicators might underestimate the number of events. Single glass shards from each deposit were geochemically characterised to trace the volcanic source and many of these deposits could be correlated between cores. We show that the 64 deposits represent tephra deposits from 42 separate volcanic events, and of these, 39 are from Iceland, two from the north Pacific region (Japan and USA) and one has an unknown source. Six deposits can be correlated to terrestrial and/or marine tephra deposits in the Northern Hemisphere and the remaining 36 are unreported in other archives. We did not locate tephra from the compositionally distinctive Laacher See eruption (∼13 ka b2k) in our records. Combining our new discoveries with the previously published tephra framework, raises the number of individual tephra horizons found in Greenland ice over this interval to 50. This significantly improves the regional tephrochronological framework, our knowledge of the eruptive history of Iceland during the LGIT and provides new tephra constraints over key LGIT climate events. Consequentially, this framework can guide sampling strategies of future tephra studies in the terrestrial and marine realms aiming to link these records to the Greenland ice cores to assess regional climate synchroneity

Self-regulation of ice flow varies across the ablation area in South-West Greenland

The concept of a positive feedback between ice flow and enhanced melt rates in a warmer climate fuelled the debate regarding the temporal and spatial controls on seasonal ice acceleration. Here we combine melt, basal water pressure and ice velocity data. Using 20 years of data covering the whole ablation area, we show that there is not a strong positive correlation between annual ice velocities and melt rates. Annual velocities even slightly decreased with increasing melt. Results also indicate that melt variations are most important for velocity variations in the upper ablation zone up to the equilibrium line altitude. During the extreme melt in 2012, a large velocity response near the equilibrium line was observed, highlighting the possibility of meltwater to have an impact even high on the ice sheet. This may lead to an increase of the annual ice velocity in the region above S9 and requires further monitoring